Identification of novel kinase inhibitors by targeting a kinase-related apoptotic protein-protein interaction network in HeLa cells

DeepSG2PPI: A Protein-Protein Interaction Prediction Method Based on Deep Learning

Protein-protein interaction (PPI) plays an important role in almost all life activities. Many protein interaction sites have been confirmed by biological experiments, but these PPI site identification methods are time-consuming and expensive. In this study, a deep learning-based PPI prediction method, named DeepSG2PPI, is developed. First, the protein sequence information is retrieved and the local context information of each amino acid residue is calculated. A two-dimensional convolutional neural network (2D-CNN) model is employed to extract features from a two-channel coding structure, in which an attention mechanism is embedded to assign higher weights to key features. Second, the global statistical information of each amino acid residue and the relationship graph between the protein and GO (Gene Ontology) function annotation are built, and the graph embedding vector is constructed to represent the biological features of the protein. Finally, a 2D-CNN model and two 1D-CNN models are combined for PPI prediction. The comparison analysis with existing algorithms shows that the DeepSG2PPI method has better performance. It provides more accurate and effective PPI site prediction, which will be helpful in reducing the cost and failure rate of biological experiments.

Association analysis of hepatocellular carcinoma-related hub proteins and hub genes

PURPOSE

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. The occurrence and development of HCC are closely related to epigenetic modifications. Epigenetic modifications can regulate gene expression and related functions through DNA methylation. This paper presents an association analysis method of HCC-related hub proteins and hub genes.

EXPERIMENTAL DESIGN

Bioinformatics analysis of HCC-related DNA methylation data is carried out to clarify the molecular mechanism of HCC-related genes and to find hub genes (genes with more connections in the network) by constructing in the gene interaction network. This paper proposes an accurate prediction method of protein-protein interaction (PPI) based on deep learning model DeepSG2PPI. The trained DeepSG2PPI model predicts the interaction relationship between the synthetic proteins regulated by HCC-related genes.

RESULTS

This paper finds that four genes are the intersection of hub genes and hub proteins. The four genes are: FBL, CCNB2, ALDH18A1, and RPLP0. The association of RPLP0 gene with HCC is a new finding of this study. RPLP0 is expected to become a new biomarker for the treatment, diagnosis, and prognosis of HCC. The four proteins corresponding to the four genes are: ENSP00000221801, ENSP00000288207, ENSP00000360268, and ENSP00000449328.

CONCLUSIONS AND CLINICAL RELEVANCE

The association between the hub genes with the hub proteins is analyzed. The mutual verification of the hub genes and the hub proteins can obtain more credible HCC-related genes and proteins, which is helpful for the diagnosis, treatment, and drug development of HCC.

Knockdown of miR-423-5p simultaneously upgrades the eNOS and VEGFa pathways in ADSCs and improves erectile function in diabetic rats

This study aimed to explore the possibility of miR‐423‐5p modified adipose‐derived stem cell (ADSCs) therapy on streptozotocin (STZ)‐induced diabetes mellitus erectile dysfunction (DMED) rats. MiR‐423‐5p was knocked down in ADSCs. ADSCs, NC‐miR‐ADSCs and miR‐ADSCs were co‐cultured with human umbilical vein endothelial cells (HUVECs). Normal and high glucose media were supplemented. The supernatant and HUVECs were collected for assessment of eNOS and VEGFa expression, cell proliferation, and apoptosis. HUVECs co‐cultured with ADSCs or miR‐ADSCs exhibited higher eNOS and VEGFa protein expression levels compared to DM groups. MiR‐ADSCs enhanced HUVEC proliferation compared to the ADSCs and NC‐miR‐ADSCs. Lower apoptotic rates were observed when HUVECs were co‐cultured with miR‐ADSCs, compared to ADSCs and NC‐miR‐ADSCs. Fifteen male Sprague‐Dawley (SD) rats aged 12 weeks were induced to develop diabetes mellitus by intraperitoneal injection with STZ, and five healthy SD rats were used as normal controls. Eight weeks after developing diabetes, the rats received ADSCs and miR‐ADSCs via injection into the corpora cavernosa, whereas normal controls and DM controls were injected with saline. Erectile function and histological assessment of penile tissues were performed 8 weeks after injection. The ICP/MAP indicated that erectile function was impaired in the DM rats compared with the normal group. Injection of ADSCs and miR‐ADSCs improved erectile function significantly and was associated with the overexpression of eNOS and VEGFa. MiR‐423‐5p knockdown in ADSCs ameliorated high glucose‐mediated damage to HUVECs and improved erectile function in DM rats by inducing eNOS and VEGFa overexpression, indicating that miR‐423‐5p may be a potential target in the treatment of DMED.

Glucocappasalin Induces G2/M-Phase Arrest, Apoptosis, and Autophagy Pathways by Targeting CDK1 and PLK1 in Cervical Carcinoma Cells

Glucocappasalin (GCP), a natural product derived from the seeds of Descurainia sophia (L.) Webb. ex Prantl, exhibits potential antitumor activity in HeLa cervical carcinoma cells. In this study, we investigated the anti-cervical cancer property of GCP through the induction of cell cycle arrest, apoptosis, and autophagy in vitro and in vivo, and elucidated the underlying molecular mechanisms. We demonstrated that treatment with GCP inhibited the growth of HeLa, Siha, and Ca Ski cell lines in a dose-dependent manner, with HeLa cells displaying particular sensitivity to the GCP treatment. Subsequently, the expression of cyclin-dependent kinase 1 (CDK1) and polo like kinase 1 (PLK1) were evaluated in HeLa cells using the CDK1 kinase assay kit, the fluorescence polarization assay, real-time quantitative PCR, and western blotting. Our results demonstrate that GCP could be employed to attenuate the expression of CDK1 and PLK1 in a dose- and time-dependent manner. The complementary results obtained by flow cytometry and western blotting allowed us to postulate that GCP may exhibit its antitumor effects by inducing G2/M cell cycle arrest. Moreover, HeLa cells treated with GCP exhibited a loss in mitochondrial membrane potential, together with the activation of caspases 3 and 9, and poly ADP-ribose polymerase (PARP). Additionally, we found that GCP could increase the formation of acidic vesicular organelles (AVOs), as well as the levels of Beclin1, LC3-II, p62, and Atg5 proteins in HeLa cells. Further studies indicated that GCP triggered autophagy via the suppression of the PI3K/AKT/mTOR signaling pathways. The autophagy inhibitor 3-methyladenine (3-MA) was used to determine whether autophagy affects the apoptosis induced by GCP. Interestingly, the inhibition of autophagy attenuated apoptosis. In vivo anti-tumor experiments indicated that GCP (60 mg/kg, i.p.) markedly reduced the growth of HeLa xenografts in nude mice without apparent toxicity. Taken together, we demonstrate that GCP induces cell cycle G2/M-phase arrest, apoptosis, and autophagy by acting on the PI3K/AKT/mTOR signaling pathways in cervical carcinoma cells. Thus, GCP may represent a promising agent in the eradication of cervical cancer.

Microbial Glycosylation of Phenanthrene and Bibenzyls by Mucor hiemalis

Microbial transformation of denthyrsinin (1), gigantol (2), and batatasin III (3), the major constituents of Dendrobium species (Orchidaceae), was performed using the filamentous fungus Mucor hiemalis KCTC 26779. Three glycosylated metabolites were obtained in the biotransformation of 1-3, and their structures were identified as denthyrsinin-6- O-β-d-glucoside (4), gigantol-5- O-β-d-glucoside (5), and batatasin III-3- O-β-d-glucoside (6) by analyzing 1-dimensional and 2-dimensional-nuclear magnetic resonance spectra, as well as high-resolution electrospray ionization mass spectral data. Among them, metabolite 4 has not been previously reported. Mucor hiemalis was revealed to catalyze enzymatically glucosylation of the hydroxyl group of phenanthrenes and bibenzyls. This research provides an efficient approach for the glycosylation of phenanthrenes and bibenzyls and can expand the library of available phenanthrene and bibenzyl derivatives for further biological evaluations.

Identification of Novel Key Targets and Candidate Drugs in Oral Squamous Cell Carcinoma

Background:

Oral Squamous Cell Carcinoma (OSCC) is the most common malignant epithelial neoplasm. It is located within the top 10 ranking incidence of cancers with a poor prognosis and low survival rates. New breakthroughs of therapeutic strategies are therefore needed to improve the survival rate of OSCC harboring patients.

Objective:

Since targeted therapy is considered as the most promising therapeutic strategies in cancer, it is of great significance to identify novel targets and drugs for the treatment of OSCC.

Methods:

A series of bioinformatics approaches were launched to identify the hub proteins and their potential agents. Microarray analysis and several online functional activity network analysis were firstly utilized to recognize drug targets in OSCC. Subsequently, molecular docking was used to screen their potential drugs from the specs chemistry database. At the same time, the assessment of ligand-based virtual screening model was also evaluated.

Results:

In this study, two microarray data (GSE31056, GSE23558) were firstly selected and analyzed to get consensus candidate genes including 681 candidate genes. Additionally, we selected 33 candidate genes based on whether they belong to the kinases and transcription factors and further clustered candidate hub targets based on functions and signaling pathways with significant enrichment analysis by using DAVID and STRING online databases. Then, core PPI network was then identified and we manually selected GRB2 and IGF1 as the key drug targets according to the network analysis and previous references. Lastly, virtual screening was performed to identify potential small molecules which could target these two targets, and such small molecules can serve as the promising candidate agents for future drug development.

Conclusion:

In summary, our study might provide novel insights for understanding of the underlying molecular events of OSCC, and our discovered candidate targets and candidate agents could be used as the promising therapeutic strategies for the treatment of OSCC.

Discovery of selective farnesoid X receptor agonists for the treatment of hyperlipidemia from traditional Chinese medicine based on virtual screening and in vitro validation

Farnesoid X receptor (FXR), a bile acid receptor, has important roles in maintaining bile acid and cholesterol homeostasis, which is an attractive target for hyperlipidemia. Present study aimed to discover potential selective FXR agonists over G-protein coupled bile acid receptor 1 (GPBAR1, TGR5) from traditional Chinese medicine (TCM) by using virtual screening, in vitro studies and molecular dynamics simulation (MD). Ligand-based pharmacophore model for FXR was firstly built to screen FXR agonists from the Traditional Chinese Medicine Database (TCMD). Then, 21 FXR crystal structures were clustered in two types and two representative structures (PDB ID: 3OMM and 3P89) were, respectively, used to carry out molecular docking to refine the screened result. Moreover, the pharmacophore model for GPBAR1 was built to screen selective FXR agonists with no activity on GPBAR1. A set of 24 candidate selective FXR agonists which fitvalue of FXR pharmacophore model and docking score of 3OMM and 3P89 were in the top 100 and cannot match the pharmacophore model for GPBAR1 were obtained. By the lipid-lowering activity test in HepG2 cell lines, Arctigenin was identified to be potential selective FXR agonist with the activity of 20 μmol·L^-1. After down-regulating FXR, Arctigenin could increase the mRNA of FXR while exerted no effect on the mRNA of GPBAR1. MD was further used to interpret the mechanism of Arctigenin with the representative structures. This research provided a new screening procedure for finding selective candidate compounds and appropriate docking models of a target by considering the structure diversity of PDB structures, which was applied to discovery novel selective FXR agonists to treat hyperlipidemia.Communicated by Ramaswamy H. Sarma.

miR-328-3p mediates the anti-tumor effect in osteosarcoma via directly targeting MMP-16

Background

Increasing reports demonstrated that dysregulated expression of microRNAs (miRNAs) leads to the progression of various tumors. Previous studies revealed that miR-328-3p exhibited dysregulated expression in various types of tumors. However, its function and underlying mechanism in osteosarcoma (OS) are still unexplored.

Methods

The expression of miR-328-3p in the tissues and OS cell lines was detected by qRT-PCR analysis. The effects of miR-328-3p in the proliferation were analyzed by MTT assay. The proliferation and apoptosis of OS cells were examined by colony formation assay and TUNEL staining respectively. The migration and tumor formation ability of OS cells were measured by wound healing assay and xenograft in vivo mice assay. Furthermore, the regulatory roles of miR-328-3p/MMP16 were determined by western blot and luciferase reporter assay.

Results

The expression of miR-328-3p was significantly decreased in OS tissues and cell lines. Furthermore, overexpression of miR-328-3p inhibited the cell proliferation and migration, but promoted the apoptosis of OS cells in vitro. Moreover, the analysis in vivo showed that miR-328-3p effectively suppressed the formation of tumors. According to the results of western blot analysis and luciferase reporter assay, we identified matrix metalloproteinase-16 (MMP-16) acted as a direct target of miR-328-3p. Moreover, the expression level of MMP-16, which participates in the occurrence and development of many cancers, was negatively correlated with the miR-328-3p expression in OS cells.

Conclusion

miR-328-3p inhibited the proliferation, migration but accelerated the apoptosis of OS by directly inhibiting MMP-16. And miR-328-3p/MMP-16 axis may be one of the mechanisms of OS development and a novel potential method for the treatment of OS in clinic.

Discovery of Novel Human Epidermal Growth Factor Receptor-2 Inhibitors by Structure-based Virtual Screening

BACKGROUND

Human epidermal growth factor receptor-2 (HER2) is a trans-membrane receptor like protein, and aberrant signaling of HER2 is implicated in many human cancers, such as ovarian cancer, gastric cancer, and prostate cancer, most notably breast cancer. Moreover, it has been in the spotlight in the recent years as a promising new target for therapy of breast cancer.

OBJECTIVE

Since virtual screening has become an integral part of the drug discovery process, it is of great significant to identify novel HER2 inhibitors by structure-based virtual screening.

MATERIALS AND METHODS

In this study, we carried out a series of elegant bioinformatics approaches, such as virtual screening and molecular dynamics (MD) simulations to identify HER2 inhibitors from Food and Drug Administration-approved small molecule drug as potential "new use" drugs.

RESULTS

Molecular docking identified top 10 potential drugs which showed spectrum affinity to HER2. Moreover, MD simulations suggested that ZINC08214629 (Nonoxynol-9) and ZINC03830276 (Benzonatate) might exert potential inhibitory effects against HER2-targeted anti-breast cancer therapeutics.

CONCLUSION

Together, our findings may provide successful application of virtual screening studies in the lead discovery process, and suggest that our discovered small molecules could be effective HER2 inhibitor candidates for further study.

SUMMARY

A series of elegant bioinformatics approaches, including virtual screening and molecular dynamics (MD) simulations were took advantage to identify human epidermal growth factor receptor-2 (HER2) inhibitors. Molecular docking recognized top 10 candidate compounds, which showed spectrum affinity to HER2. Further, MD simulations suggested that ZINC08214629 (Nonoxynol-9) and ZINC03830276 (Benzonatate) in candidate compounds were identified as potential "new use" drugs against HER2-targeted anti-breast cancer therapeutics. Abbreviations used: HER2: Human epidermal growth factor receptor-2, FDA: Food and Drug Administration, PDB: Protein Database Bank, RMSDs: Root mean square deviations, SPC: Single point charge, PME: Particle mesh Ewald, NVT: Constant volume, NPT: Constant pressure, RMSF: Root-mean-square fluctuation.

Identification of Novel Pathways in Plant Lectin-Induced Cancer Cell Apoptosis

Plant lectins have been investigated to elucidate their complicated mechanisms due to their remarkable anticancer activities. Although plant lectins seems promising as a potential anticancer agent for further preclinical and clinical uses, further research is still urgently needed and should include more focus on molecular mechanisms. Herein, a Naïve Bayesian model was developed to predict the protein-protein interaction (PPI), and thus construct the global human PPI network. Moreover, multiple sources of biological data, such as smallest shared biological process (SSBP), domain-domain interaction (DDI), gene co-expression profiles and cross-species interolog mapping were integrated to build the core apoptotic PPI network. In addition, we further modified it into a plant lectin-induced apoptotic cell death context. Then, we identified 22 apoptotic hub proteins in mesothelioma cells according to their different microarray expressions. Subsequently, we used combinational methods to predict microRNAs (miRNAs) which could negatively regulate the abovementioned hub proteins. Together, we demonstrated the ability of our Naïve Bayesian model-based network for identifying novel plant lectin-treated cancer cell apoptotic pathways. These findings may provide new clues concerning plant lectins as potential apoptotic inducers for cancer drug discovery.